A new algorithm to speed up elastic matching face recognition algorithm was presented.Elastic matching has relatively higher recognition rate but also higher calculation complexity,which limits its application.The main idea of Classified Elastic Matching(CEM) is as follows.Regard grid translation,which is one of the two steps of elastic matching,as an independent matching algorthm.To all candidate face images,do grid translation and calculate corresponding Coarse Matching Score(CMS) at first.Align the candidates in descending order according to CMS.Only to grid distortions to these face images having relatively higher CMS values.Experimental results based on a large database including face images from 100 180 individuals show that the time cost of grid translation in CEM is more than 1 000 times reduced compared to that in traditional elastic matching with recognition rate depressed less than 0.5%.